Article
Engineering, Multidisciplinary
Slavica Prvulovic, Predrag Mosorinski, Dragica Radosav, Jasna Tolmac, Milica Josimovic, Vladimir Sinik
Summary: This article discusses the process of determining the working temperature of the workpiece in the cutting zone when machining plastic on a lathe. The application and programming of a fuzzy logic controller (FLC) can help maintain the processing temperature of the workpiece below 100 degrees C. Experimental results demonstrate the generation of acceptable temperature values for polytetrafluoroethylene (PTFE), also known as teflon, using the fuzzy logic controller.
AIN SHAMS ENGINEERING JOURNAL
(2022)
Article
Energy & Fuels
Hossam S. Salama, Abualkasim Bakeer, Istvan Vokony, Andrii Chub
Summary: This paper presents an effective solution to mitigate the frequency and voltage fluctuations caused by the integration of the pulsed power load (PPL) into the power system, using a superconducting magnetic energy storage (SMES) system with fuzzy logic control technique. The proposed system shows high performance in minimizing voltage and frequency fluctuations during the operation of PPL.
Article
Computer Science, Information Systems
Omer Ali Abubakr, Mohammad A. A. Jaradat, Mamoun F. F. Abdel-Hafez
Summary: The paper presents an adaptive dynamic window approach with a fuzzy logic controller for mobile robot dynamic obstacles avoidance. The proposed method optimizes the objective function weights to make the robot more resilient to changes and move towards the goal as fast as possible. Experimental results show that the proposed method significantly improves the success rate in both static and dynamic environments.
Review
Mathematics
Hadi Jahanshahi, Zahra Alijani, Sanda Florentina Mihalache
Summary: Modern requirements demand sustainable transportation systems due to the significant growth in transportation activities, which is expected to continue, leading to environmental concerns such as pollution and noise. To address this crisis, municipal administrations are investing in sustainable, reliable, economical, and eco-friendly transportation systems. This review discusses the latest developments in fuzzy decision systems for sustainable transport supplements. By examining literature, the review evaluates the serviceability of the entire supply chain to ensure transport quality, eliminate degradation, and meet customer demands. The connection between fuzzy decision systems and supply chain serviceability may not be immediately obvious, but integrating them can provide valuable focus for companies. By leveraging fuzzy decision systems to optimize supply chain processes and improve service levels, companies can gain a competitive advantage and better meet customer demand.
Article
Computer Science, Artificial Intelligence
Mohamed Barakat
Summary: This paper proposes a fuzzy logic controller (FLC) structure and its input-output relationship rules for designing a secondary controller to address load frequency control (LFC) issues. The FLC is coupled with a proportional-integral-derivative (PID) controller, forming the proposed FPID controller. Simulations on various models demonstrate that the proposed FPID controller outperforms other techniques in terms of peaks and settling time.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Automation & Control Systems
Yue-Jiao Gong, Yi-Wen Liu, Ying Lin, Wei-Neng Chen, Jun Zhang
Summary: This paper presents a two-stage taxi-passenger matching system that optimizes the quality and profit of taxi-passenger matching by utilizing a fuzzy controller and a polynomial Kuhn-Munkres algorithm.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Agronomy
Romeo Urbieta Parrazales, Maria T. Zagaceta Alvarez, Karen A. Aguilar Cruz, Rosaura Palma Orozco, Jose L. Fernandez Munoz
Summary: The study introduces a fuzzy logic controller (FLC) system for optimizing irrigation of rose crops by controlling relative humidity and temperature. The implementation of the FLC system has shown a significant reduction in water consumption and operational costs in practice.
Article
Computer Science, Artificial Intelligence
Nitidetch Koohathongsumrit, Wasana Chankham
Summary: This study proposes a new hybrid decision-making framework that integrates the fuzzy risk assessment model (FRAM), best-worst method (BWM), and measurement of alternatives and ranking according to the compromise solution (MARCOS) to select the optimal transportation route in multimodal supply chains. The framework effectively optimizes the route selection problem and assists decision makers in developing new interactive freight distribution plans and transportation policies.
APPLIED SOFT COMPUTING
(2023)
Article
Multidisciplinary Sciences
Parimala Arumugam, Srinath Subbaraman, Kannan Chandrasekaran
Summary: This research article presents a modified novel crisscross augmented ladder (CCAL) structured multilevel inverter (MLI) that can operate in various voltage ratios. The modified structure reduces the conduction path of active switches, leading to benefits such as lower switch stress and loss. The article also introduces a control scheme with a fuzzy logic controller, which further reduces switch stress and loss.
Article
Computer Science, Information Systems
Bikash Sah, Praveen Kumar, Sanjay Kumar Bose
Summary: As the usage of electric vehicles (EVs) increases for mobility, the demand for power from the electric grid is expected to rise, leading to the emergence of Vehicle to Grid (V2G) technology. The V2G controller plays a crucial role in determining the power exchange between EVs and the grid, with this article proposing an intelligent controller framework based on data integrity and correction checks.
IEEE SYSTEMS JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Dragana J. Petrovic, Miroslav M. Lazic, Bojana V. Jovanovic Lazic, Branko D. Blanusa, Stanko O. Aleksic
Summary: This paper introduces a novel power supply system that utilizes fuzzy inference logic to enhance the control of renewable energy sources. The system integrates solar and wind sources, along with an accumulator battery as an additional power source. By parallel connecting multiple energy sources, the system ensures stable power supply and optimal charging. The system uses two serial converters and a fuzzy logic controller to control the parallel connection of the renewable energy sources, and the reference voltage control of the converters enables optimal utilization of the available energy sources. The accumulated battery compensates for any shortage of solar and wind energies, and excess energy is stored in the battery. Experimental measurements were conducted on a prototype system under real conditions and compared with existing systems of similar nature. This innovative system is primarily designed for remote telecom locations that lack a power distribution network.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2022)
Article
Engineering, Electrical & Electronic
J. C. Vinitha, Geetha Ramadas, P. Usha Rani
Summary: Electric vehicles are favored for their environmentally friendly nature and preservation of natural resources. Research on electric vehicle charging stations has focused on technical and economic feasibility, with a few studies considering power fluctuations caused by load variations. This study proposes an optimization-based feasp for controlling power fluctuations using an Enhanced Particle Swarm Optimization based Fuzzy Logic Controller (FLC), which effectively reduces fluctuations and stabilizes the system in the shortest time. Comparison with conventional methods justifies the effectiveness of the proposed controller tuning.
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
(2023)
Article
Automation & Control Systems
Abdulhamit Nurettin, Nihat Inanc
Summary: In order to improve the speed control performance of a three-phase induction motor controlled by the vector control strategy, a new design of a hybrid controller (HC) based on the supertwisting algorithm (STA) and fuzzy approach is proposed. The HC includes a fuzzy logic control approach to online self-tune the control gains and a supertwisting sliding mode load disturbance observer to estimate the load torque disturbances. The proposed scheme is validated to be superior to advanced and traditional controllers in simulation and experimental studies.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Automation & Control Systems
Anupam Kumar, Ritu Raj, Amit Kumar, Bharat Verma
Summary: This paper proposes a novel coupling-based mixed interval type-2 fuzzy logic controller (MIT2FLC) for trajectory tracking problems of complex robot manipulator plants. The controller addresses the issue of coupling between robotic links during operation and effectively deals with uncertainty and provides robust performance. The Grey wolf optimization (GWO) is utilized to calculate the optimal parameters of the controller. Comparative analysis is conducted with type-1 fuzzy logic controllers (MT1FLC, T1FLC) and PID controllers to evaluate the performance of the MIT2FLC approach. Robustness analysis is performed for external disturbances, varying system parameters, and random noise.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Automation & Control Systems
Soumyadeep Samonto, Samarjit Kar, Sagarika Pal, Ozkan Atan, Arif Ahmed Sekh
Summary: This paper discusses an intelligent relaying scheme based on expert systems and fuzzy algorithms to control multiple loads connected to a single feeder line. Through testing and validation, the fastest coordination time was successfully achieved under the IEEE 13 Bus system.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Green & Sustainable Science & Technology
Neeraj Bhanot, P. Venkateswara Rao, S. G. Deshmukh
CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY
(2016)
Article
Engineering, Mechanical
Ajith Tom James, Om Parkash Gandhi, Sanjeev Govindrao Deshmukh
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
(2017)
Article
Green & Sustainable Science & Technology
Neeraj Bhanot, P. Venkateswara Rao, S. G. Deshmukh
JOURNAL OF CLEANER PRODUCTION
(2017)
Article
Computer Science, Artificial Intelligence
Vedpal Arya, S. G. Deshmukh, Naresh Bhatnagar
JOURNAL OF INTELLIGENT MANUFACTURING
(2019)
Article
Computer Science, Interdisciplinary Applications
Vedpal Arya, S. G. Deshmukh, Naresh Bhatnagar
COMPUTERS & INDUSTRIAL ENGINEERING
(2019)
Letter
Emergency Medicine
Abid Haleem, Mohd Javaid, Raju Vaishya, S. G. Deshmukh
AMERICAN JOURNAL OF EMERGENCY MEDICINE
(2020)
Article
Management
Shahbaz Khan, Abid Haleem, S. G. Deshmukh, Mohd Javaid
Summary: This study aims to identify and discuss the significant impact of COVID-19 on the current supply chain, particularly the medical supply chain. It recommends potential solution measures to reduce the impact of COVID-19 on the existing supply chain and suggests management develop an action plan for early recovery.
JOURNAL OF INDUSTRIAL INTEGRATION AND MANAGEMENT-INNOVATION AND ENTREPRENEURSHIP
(2021)
Article
Engineering, Multidisciplinary
Ajith Tom James, O. P. Gandhi, S. G. Deshmukh
INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT
(2018)
Article
Engineering, Multidisciplinary
Sufian Yousef, Haider Albonda, Shashikala Tapaswi, Michael Cole, Sanjeev Deshmukh
INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT
(2017)
Article
Engineering, Multidisciplinary
Ajith Tom James, O. P. Gandhi, S. G. Deshmukh
INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT
(2017)
Article
Management
Neeraj Bhanot, P. Venkateswara Rao, S. G. Deshmukh
JOURNAL OF ADVANCES IN MANAGEMENT RESEARCH
(2016)
Proceedings Paper
Engineering, Industrial
Nitin Kumar Upadhye, S. G. Deshmukh, Suresh Garg, Durgesh Sharma
2015 INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND OPERATIONS MANAGEMENT (IEOM)
(2015)
Proceedings Paper
Management
Neeraj Bhanot, P. Venkateswara Rao, S. G. Deshmukh
OPERATIONS MANAGEMENT IN DIGITAL ECONOMY
(2015)
Proceedings Paper
Management
Vedpal Arya, S. G. Deshmukh, Naresh Bhatnagar
OPERATIONS MANAGEMENT IN DIGITAL ECONOMY
(2015)
Article
Management
Ajith Tom James, O. P. Gandhi, S. G. Deshmukh
JOURNAL OF ADVANCES IN MANAGEMENT RESEARCH
(2017)
Review
Computer Science, Artificial Intelligence
Wei Gao, Shuangshuang Ge
Summary: This study provides a comprehensive review of slope stability research based on artificial intelligence methods, focusing on slope stability computation and evaluation. The review covers studies using quasi-physical intelligence methods, simulated evolutionary methods, swarm intelligence methods, hybrid intelligence methods, artificial neural network methods, vector machine methods, and other intelligence methods. The merits, demerits, and state-of-the-art research advancement of these studies are analyzed, and possible research directions for slope stability investigation based on artificial intelligence methods are suggested.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Khuong Le Nguyen, Hoa Thi Trinh, Saeed Banihashemi, Thong M. Pham
Summary: This study investigated the influence of input parameters on the shear strength of RC squat walls and found that ensemble learning models, particularly XGBoost, can effectively predict the shear strength. The axial load had a greater influence than reinforcement ratio, and longitudinal reinforcement had a more significant impact compared to horizontal and vertical reinforcement. The performance of XGBoost model outperforms traditional design models and reducing input features still yields reliable predictions.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Bo Hu, Huiyan Zhang, Xiaoyi Wang, Li Wang, Jiping Xu, Qian Sun, Zhiyao Zhao, Lei Zhang
Summary: A deep hierarchical echo state network (DHESN) is proposed to address the limitations of shallow coupled structures. By using transfer entropy, candidate variables with strong causal relationships are selected and a hierarchical reservoir structure is established to improve prediction accuracy. Simulation results demonstrate that DHESN performs well in predicting algal bloom.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Limin Wang, Lingling Li, Qilong Li, Kuo Li
Summary: This paper discusses the urgency of learning complex multivariate probability distributions due to the increase in data variability and quantity. It introduces a highly scalable classifier called TAN, which utilizes maximum weighted spanning tree (MWST) for graphical modeling. The paper theoretically proves the feasibility of extending one-dependence MWST to model high-dependence relationships and proposes a heuristic search strategy to improve the fitness of the extended topology to data. Experimental results demonstrate that this algorithm achieves a good bias-variance tradeoff and competitive classification performance compared to other high-dependence or ensemble learning algorithms.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Zhejing Hu, Gong Chen, Yan Liu, Xiao Ma, Nianhong Guan, Xiaoying Wang
Summary: Anxiety is a prevalent issue and music therapy has been found effective in reducing anxiety. To meet the diverse needs of individuals, a novel model called the spatio-temporal therapeutic music transfer model (StTMTM) is proposed.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Nur Ezlin Zamri, Mohd. Asyraf Mansor, Mohd Shareduwan Mohd Kasihmuddin, Siti Syatirah Sidik, Alyaa Alway, Nurul Atiqah Romli, Yueling Guo, Siti Zulaikha Mohd Jamaludin
Summary: In this study, a hybrid logic mining model was proposed by combining the logic mining approach with the Modified Niche Genetic Algorithm. This model improves the generalizability and storage capacity of the retrieved induced logic. Various modifications were made to address other issues. Experimental results demonstrate that the proposed model outperforms baseline methods in terms of accuracy, precision, specificity, and correlation coefficient.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
David Jacob Kedziora, Tien-Dung Nguyen, Katarzyna Musial, Bogdan Gabrys
Summary: The paper addresses the problem of efficiently optimizing machine learning solutions by reducing the configuration space of ML pipelines and leveraging historical performance. The experiments conducted show that opportunistic/systematic meta-knowledge can improve ML outcomes, and configuration-space culling is optimal when balanced. The utility and impact of meta-knowledge depend on various factors and are crucial for generating informative meta-knowledge bases.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
G. Sophia Jasmine, Rajasekaran Stanislaus, N. Manoj Kumar, Thangamuthu Logeswaran
Summary: In the context of a rapidly expanding electric vehicle market, this research investigates the ideal locations for EV charging stations and capacitors in power grids to enhance voltage stability and reduce power losses. A hybrid approach combining the Fire Hawk Optimizer and Spiking Neural Network is proposed, which shows promising results in improving system performance. The optimization approach has the potential to enhance the stability and efficiency of electric grids.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Zhijiang Wu, Guofeng Ma
Summary: This study proposes a natural language processing-based framework for requirement retrieval and document association, which can help to mine and retrieve documents related to project managers' requirements. The framework analyzes the ontology relevance and emotional preference of requirements. The results show that the framework performs well in terms of iterations and threshold, and there is a significant matching between the retrieved documents and the requirements, which has significant managerial implications for construction safety management.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Yung-Kuan Chan, Chuen-Horng Lin, Yuan-Rong Ben, Ching-Lin Wang, Shu-Chun Yang, Meng-Hsiun Tsai, Shyr-Shen Yu
Summary: This study proposes a novel method for dog identification using nose-print recognition, which can be applied to controlling stray dogs, locating lost pets, and pet insurance verification. The method achieves high recognition accuracy through two-stage segmentation and feature extraction using a genetic algorithm.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Shaohua Song, Elena Tappia, Guang Song, Xianliang Shi, T. C. E. Cheng
Summary: This study aims to optimize supplier selection and demand allocation decisions for omni-channel retailers in order to achieve supply chain resilience. It proposes a two-phase approach that takes into account various factors such as supplier evaluation and demand allocation.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Jinyan Hu, Yanping Jiang
Summary: This paper examines the allocation problem of shared parking spaces considering parking unpunctuality and no-shows. It proposes an effective approach using sample average approximation (SAA) combined with an accelerating Benders decomposition (ABD) algorithm to solve the problem. The numerical experiments demonstrate the significance of supply-demand balance for the operation and user satisfaction of the shared parking system.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Computer Science, Artificial Intelligence
Soroor Motie, Bijan Raahemi
Summary: Financial fraud is a persistent problem in the finance industry, but Graph Neural Networks (GNNs) have emerged as a powerful tool for detecting fraudulent activities. This systematic review provides a comprehensive overview of the current state-of-the-art technologies in using GNNs for financial fraud detection, identifies gaps and limitations in existing research, and suggests potential directions for future research.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Computer Science, Artificial Intelligence
Enhao Ning, Changshuo Wang, Huang Zhang, Xin Ning, Prayag Tiwari
Summary: This review provides a detailed overview of occluded person re-identification methods and conducts a systematic analysis and comparison of existing deep learning-based approaches. It offers important theoretical and practical references for future research in the field.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Jiajun Ma, Songyu Hu, Jianzhong Fu, Gui Chen
Summary: The article presents a novel visual hierarchical attention detector for multi-scale defect location and classification, utilizing texture, semantic, and instance features of defects through a hierarchical attention mechanism, achieving multi-scale defect detection in bearing images with complex backgrounds.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)